Machine Learning Engineer

Machine Learning Engineer
ROLE PROFILE
• Designs and develops scalable machine learning models and AI-driven
solutions to address complex business challenges and enhance decision-
making processes
KEY RESPONSIBILITIES
• Work with large and complex data sets to solve challenging business
problems
• Efficient training and deployment of standard ML, NN, and Agentic models.
• Develop, train, and optimize machine learning models using state-of-the-art
algorithms and frameworks
• Build production grade end-to-end ML pipelines, including data ingestion,
transformation, model training, validation, and deployment
• Automate workflows for model training, testing, and deployment using
CI/CD pipelines and MLOps tools
• Collaborate with cross-functional teams to integrate models into applications
and deliver end-to-end solutions
• Finetune SLMs/LLMs and build complex AI architectures

PROFESSIONAL EXPERIENCE/QUALIFICATIONS
• (3-7) years of experience in building production grade, scalable AI systems.
• Expert in supervised/unsupervised learning, deep learning, NLP, computer
vision, or generative AI (e.g., LLMs).
• Strong ML system architecture skills
• Understanding of model serving, API development (FastAPI, Flask), and
optimizing model performance for real-time or batch inference.
• General Knowledge of Docker, Kubernetes, CI/CD pipelines, and tools like
MLflow/Kubeflow for model lifecycle management (MLOps)
• Comfortable with deploying models on AWS or Azure
• Minimum Educational qualifications: Bachelor’s degree in Computer Science,
Engineering, or related field required
• Preferred Education qualifications: Master or PhD in Computer Science or a
related field. -